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. Author manuscript; available in PMC: 2022 Dec 7.
Published in final edited form as: Psychol Trauma. 2022 Apr 28;14(8):1304–1313. doi: 10.1037/tra0001224

Acute Stress, Worry, and Impairment in Healthcare and Non-Healthcare Essential Workers during the COVID-19 Pandemic

Dana Rose Garfin 1,2, Lindita Djokovic 3, Roxane Cohen Silver 2,4,5, E Alison Holman 2,4
PMCID: PMC9728043  NIHMSID: NIHMS1759491  PMID: 35482684

Abstract

Objective:

Healthcare and non-healthcare essential workers working in face-to-face interactions during COVID-19 may be vulnerable to psychosocial distress. Limited empirical research on COVID-19-related psychosocial outcomes has utilized probability-based samples including both healthcare and non-healthcare essential workers.

Method:

We surveyed a sample of 1,821 United States self-identified essential workers, collected using probability-based methods, working in face-to-face interactions during the early phase of the COVID-19 outbreak (3/18/20–4/18/20), in three consecutive 10-day cohorts. We assessed acute stress, health-related worries, and functional impairment. Demographics, secondary stressors (lack of childcare or healthcare, lost wages), and pre-COVID-19 mental and physical health were examined as predictors of psychological outcomes.

Results:

Acute stress (β=.08, p=.001), health-related worries (β=.09, p=.001), and functional impairment (β=.05, p=.034) increased over time in the early weeks of the outbreak. Healthcare-essential workers reported lower functional impairment (β= −.06, p=.009) and acute stress (β =−.05, p=.015) compared to non-healthcare essential workers. Across the sample, prior mental and physical health ailments, inability to obtain health insurance, lost wages, younger age, female gender, and Hispanic ethnicity were associated with acute stress (βs=−.14 to .15, ps≤.001), health-related worries (βs=−.09–.14, ps≤.001), and functional impairment (βs=−.08 to .16, ps≤.006). Lack of childcare (β=.09, p<.001) was positively associated with acute stress.

Conclusion:

Non-healthcare essential workers may be vulnerable to negative psychosocial outcomes. Targeted training and support may help facilitate coping with the effects of working in-person during the ongoing COVID-19 pandemic. Findings may help inform intervention efforts, critical as COVID-19 becomes endemic and society must learn to live with its evolving variants.

Keywords: COVID-19, acute stress, essential workers, mental health, functional impairment

On March 13, 2020, the White House declared the COVID-19 outbreak a national emergency, its protracted duration and associated psychosocial impact unforeseeable. State officials issued sweeping stay-at-home orders that exempted essential workers including healthcare workers, caregivers, and grocery store employees, as well as workers in other sectors whose jobs required in-person interactions with social distancing guidelines difficult or impossible to maintain (Lai et al., 2020; Shanafelt et al., 2020). The empirical literature on psychosocial responses to COVID-19 among essential workers has primarily focused on caregivers and healthcare workers (Lai et al., 2020; Shanafelt et al., 2020), largely neglecting the experiences of non-healthcare essential workers.

Even during the most stringent COVID-19-related restrictions, many essential workers continued in-person work, often due to lack of job security or paid leave, and sometimes without health insurance, amplifying COVID-19-relevant worries about one’s health and safety (Shanafelt et al., 2020). Despite the increasing availability of vaccines, COVID-19 has remained a threat, due to emerging variants such as the Delta variant (Christie et al., 2021) and vaccine hesitancy (Kofman et al., 2021). As COVID-19 becomes endemic, those on the front lines will be forced to adapt and respond to the ongoing threat of COVID-19 (Kofman et al., 2021).

Research conducted during COVID-19 has demonstrated that healthcare workers are at risk for psychosocial maladies (Benfante et al., 2020), particularly those working on the front lines (Lai et al., 2020). While this relationship has been demonstrated during prior viral outbreaks (Cabarkapa et al., 2020), during COVID-19 these concerns have been exacerbated for non-healthcare, public-facing occupations as well: like healthcare workers, essential workers from other industries are at increased risk for COVID-19 infection due to frequent interactions with the public (Baker et al., 2020). Thus, there has been a growing concern to manage the physical and psychological health of all frontline workers (Sim, 2020), critical for effective workplace performance (Wright & Cropanzano, 2000) when essential tasks must be sustained. In sum, it is important to understand the psychosocial experience of workers from both healthcare and non-healthcare sectors critical for societal functioning during the COVID-19 pandemic and as society prepares for future viral threats, which science suggest will increase in the years ahead (Rogalski et al., 2017).

Healthcare Essential Workers

Research on psychosocial outcomes in healthcare essential workers during COVID-19 has proliferated, yet a clearer understanding of specific risk factors associated with psychosocial maladies may further guide research and recommendations. Meta-analytic findings regarding mental health in healthcare workers (including doctors, nurses, and other medical personnel) during the early phase of COVID-19 (e.g., before mid-April, 2020) reported a 23% prevalence of clinically significant anxiety, although these rates were comparable to that of the general public, and at the lower end of what was reported in healthcare workers during the MERS and SARS outbreaks (Pappa et al., 2020). In a rapid review of COVID-19’s impact on healthcare worker’s mental health, concerns over family health and safety, in addition to fear of infection, were risk factors for adverse mental health outcomes (De Kock et al., 2021). A recent literature review of the mental health of frontline healthcare workers employed during viral outbreaks revealed that persistent, generalized stress was associated with subsequent downstream problems including panic attacks, insomnia, and burnout (Magill et al., 2020). Internationally, healthcare essential workers who continued working during the pandemic also screened positive for moderate to extremely severe stress, psychological distress (Chew, Lee, et al., 2020), and PTSD (Tan et al., 2021). While data has illustrated that factors associated with patient care (e.g., direct work with COVID-19 patients) are associated with psychological burdens such as anxiety in healthcare workers (Lai et al., 2020), few samples have been drawn from representative samples or included comparisons with non-healthcare essential workers.

Research on healthcare worker mental health during prior viral epidemics revealed mental health ailments like acute stress disorder increased in frequency, particularly when certain sociodemographic (i.e., younger age and female gender) and occupational (i.e., high-risk roles) factors were present (Serrano-Ripoll et al., 2020). More recently, history of poor physical health (Chew Ngiam, et al., 2020; De Kock et al., 2021; Tan et al., 2020) and prior psychiatric diagnoses (Elbay et al., 2020) have been recognized as additional risk factors for COVID-19-related psychological distress in healthcare workers, which may have implications for present functioning and downstream physical and mental health (Garfin et al., 2018).

Non-healthcare Essential Workers

During strict stay-at-home restrictions in the U.S. during Spring, 2020, many non-healthcare essential workers (e.g., food service or transportation workers) continued to engage with the public, at times with little work flexibility and high risk of contracting COVID-19 (Sim, 2020). Such employees often work with less stringent protective protocols (Steege et al., 2009) than healthcare sector workers. As the economy remains open, vaccine hesitancy persists, (Sallam, 2021), vaccination rates are well-below targets, and new variants impose increasing risk to frontline works (Christie et al., 2021), understanding predictors of distress and impairment in essential workers is critical. Global research using non-probability-based samples found non-healthcare workers have continually reported adverse psychosocial outcomes during the COVID-19 pandemic. For example, up to 50% of Indian migrant workers screened positive for anxiety (Grover et al., 2020) and 65.1% of Spanish non-healthcare essential workers endorsed psychological distress (i.e., constantly feeling overwhelmed and stressed) during the early phase of the COVID-19 pandemic (Ruiz-Frutos et al., 2021). Moreover, non-healthcare essential workers have also reported health-related worries, with loved ones dying from COVID-19 and the health and well-being of family/loved ones indicated as top COVID-19-related concerns (Toh et al., 2021). Research using representative probability-based samples could strengthen inferences and elucidate key predictors of such maladies.

Some empirical literature suggests that non-healthcare essential workers actively employed during the COVID-19 pandemic are also at risk for psychological maladies, and in some cases potentially at greater risk than healthcare workers. Recent research on COVID-19 has demonstrated that some those in non-healthcare occupations (i.e., agricultural workers) report higher generalized distress symptom scores compared to other groups, including those working in healthcare industries (Tian et al., 2020). Similarly, in a sample of Australian workers, Australian non-healthcare workers reported significantly higher levels of anxiety, stress, and significantly lower quality of life compared to healthcare workers (Toh et al., 2021). Yet a community-based sample in Turkey indicated healthcare workers were more distressed than the general public (Hacimusalar et al., 2020). The present study seeks to extend this work in a U.S. sample by using a methodologically rigorous design (i.e., probability-based sampling), drawing from prior literature on disaster psychology to account for additional risk factors.

Secondary Stressors

Secondary stressors are individual-level events (e.g., personal injury or illness, loss of a job) that occur as part of a disaster cascade (Garfin et al., 2014). Exposure to greater numbers of secondary stressors has been associated with greater psychological distress following prior collective traumas including earthquakes (Garfin et al., 2014), hurricanes (Galea et al., 2007), and other natural disasters (Kessler et al., 2012). Less is known about how exposure to secondary stressors during a collective trauma like the COVID-19 pandemic may exacerbate psychosocial responses, particularly among essential workers. Data collected during the early phase of COVID-19 found some secondary stressors occurred for a substantial minority of respondents; for example, inability to obtain healthcare was associated with serious psychological distress (i.e., feeling nervous, restless, or hopeless) (McGinty et al., 2020). In a community-based sample that included healthcare and non-healthcare workers, secondary stressors including difficulties finding childcare were positively associated with anxiety (Hacimusalar et al., 2020). Early research also highlighted economic stressors as an additional risk factor for distress, such as financial loss, which during the early phases of the pandemic appeared to amplify psychological distress in the general population (Zheng et al., 2021). As the COVID-19 pandemic persisted, those unable to work from home may have been vulnerable to these stressors, which may have correlated with adverse psychosocial outcomes.

Pre-existing Mental and Physical Health Vulnerabilities

Elevated risk of severe COVID-19-related complications and mortality for individuals with pre-existing physical health conditions has been highly publicized (Flaherty et al., 2020), potentially eliciting worry, distress and impairment in those with such vulnerabilities. This was evident during prior viral outbreaks: in a systematic review on the impact of viral epidemics on mental health outcomes, chronic illness was identified as a high-risk factor for experiencing psychiatric symptoms (Luo et al., 2020). Pre-event mental health diagnoses (e.g., anxiety disorders and mood disorders) may also portended greater problems: for example, prior mental health ailments were associated with psychological distress and functional impairment following the 2014 Ebola public health crisis (Thompson et al., 2017). During COVID-19 specifically, such ailments were associated with COVID-19 related stress and traumatic stress symptoms, respectively, among American and Canadian adults (Asmundson et al., 2020). In healthcare workers, pre-COVID-19 psychological treatment increased the risk for developing COVID-19-related post-traumatic distress and anxiety by 2.5 times (Asmundson et al., 2020). These findings demonstrate the importance of evaluating pre-existing physical and mental health ailments as potential risk factors for maladaptive psychosocial outcomes during COVID-19.

Demographic Risk Factors

Demographic risk factors may also correlate with psychological distress and impairment in essential workers, potentially exacerbating existing health disparities (Kantamneni, 2020). For example, racial/ethnic minorities often encounter more COVID-19 related occupational inequalities (e.g., high-exposure occupations) and discrimination (Kantamneni, 2020), potentially leading to worse mental health outcomes. Lower income negatively correlates with deleterious psychosocial outcomes; for example, individuals who lost income due to COVID-19 reported higher hopelessness and anxiety compared to those who did not lose income (Hacimusalar et al., 2020). Low educational attainment may also place low-wage workers at more physical risk during COVID-19 (Gallagher et al., 2021). Finally, research demonstrates female healthcare essential workers face higher risks for maladaptive mental health outcomes during COVID-19 compared to their male counterparts (Cabarkapa et al., 2020; Elbay et al., 2020; Lai et al., 2020; Pappa et al., 2020).

Other demographic indicators may also portend increased vulnerability to psychosocial maladies. Despite reports that older frontline workers actively working during COVID-19 were more vulnerable to death and infection (Ghilarducci & Farmand, 2020), research has consistently shown younger workers report higher psychological distress compared to older workers (Ruiz-Frutos et al., 2021). Regional variation, a potential proxy for level of community transmission and severity of the outbreak (e.g., hospitalization and death rates), may also differentially predict psychosocial distress. Specifically, as the epidemic first spread across the United States, medical personnel in the New York Metropolitan Area were overwhelmed due to an influx of infected individuals and a lack of resources to support them (Konda et al., 2020).

The Present Study

As society continues to struggle to protect workers during the ongoing and continually evolving COVID-19 pandemic (Kofman et al., 2021), it is critical to understand experiences of essential workers who engage with the public and are at increased risk for infection. As such, the objective of the present study was to examine key theoretically and empirically derived predictors of psychosocial responses during COVID-19 among a sample of U.S. healthcare and non-healthcare essential workers still working in face-to-face interaction in the first months of the pandemic. We sought to improve upon the limited extant research by utilizing a probability-based sample, collected as the pandemic escalated in the U.S. We had one hypothesis and one exploratory aim. We hypothesized that pre-existing physical and mental health ailments and key secondary stressors would be associated with greater health-related worry, functional impairment, and acute stress, controlling for demographic risk factors. Given prior mixed research, as an exploratory aim we examined whether healthcare essential workers would report worse outcomes than non-healthcare essential workers.

Method

Sample and Procedure

Our study was conducted among a national sample of Americans using the NORC AmeriSpeak Panel, a probability-based panel of 35,000 U.S. households. NORC’s AmeriSpeak Panel randomly selected participants from their panel to form a representative sample of U.S. households. Sample stratification promoted representativeness for age, gender, race/ethnicity, and education. NORC notified participants via email when the confidential, 20-minute survey was available. Three consecutive cohorts of panelists participated in the study. There was a 10-day fielding period among each of three cohorts: Cohort 1 (3/18/20–3/28/20), Cohort 2 (3/29/20–4/7/20), and Cohort 3 (4/8/20–4/18/20). In total, 6,514 participants completed the survey (58.5% completion rate) across all cohorts with 85% responding within three days through computers (44%), smartphones (54%), and tablets (2%). Some procedures helped ensure valid survey responses. Respondents were removed from the main survey if they completed the survey in under 1/3 of the median duration and/or skipped more than 50% of the questions shown to them. Three respondents from Cohort 2 were removed since they completed the survey during the Cohort 1 timeframe and were not counted toward the total number of interviews delivered. All procedures were approved by the Institutional Review Board of University of California, Irvine; informed consent was obtained. A small compensation was provided (cash equivalent $4). See appendix for full list of measures used in these analyses.

From the full sample, a subsample of healthcare and non-healthcare essential workers was identified based on responses to several items. First, a subsample of healthcare workers was identified. As part of the profile data collected by NORC, panelist identify their employment type based on U.S. Bureau of Labor statistics identified 24 categories, including “Healthcare Practitioners and Technical Occupations.” Occupations include physicians, paramedics, psychiatrists, nurses, surgical assistants, and physician assistants. (Full list of included occupations is available at https://www.bls.gov/oes/current/oes290000.htm.) Next, participants reported whether their job required in-person interaction and they were still working (n=1,525). Participants also reported whether they were an essential worker asked to work extra hours (n=981). Six hundred eighty-five participants endorsed both items, generating a final sample of “essential workers” (n=1,821), of which 9.28% (n=169) identified as healthcare workers.

Independent Variables

Secondary stressors.

Three items assessed COVID-19 related secondary stressors: lost wages, needing childcare due to COVID-19-related school closures, and inability to obtain healthcare due to COVID-19. Items were coded 0 (not experienced) or 1 (experienced).

Prior physical and mental health ailments.

NORC collected health information history from participants prior to January 2020, before the official U.S. COVID-19 outbreak announcement. Respondents were asked whether they had been diagnosed with physical health ailments (i.e., diagnoses of high cholesterol, hypertension, diabetes/high blood sugar, heart disease, stroke, cancer, lung disease, and other diagnoses). Prior physical health diagnoses were summed into an 8-item count variable. Respondents also reported previous mental health diagnoses (anxiety, depression, or any other emotional, nervous, or psychiatric diagnosis). Prior mental health diagnoses were coded 0 (none) or 1 (prior anxiety, depression, or other emotional/nervous/psychiatric diagnosis). These variables have been used in prior research (Holman et al., 2020).

Demographics.

NORC collected demographic information (age, race/ethnicity, education, gender, income, and geographic region of residence) when participants enrolled into in the AmeriSpeak panel (updated annually for accuracy). Race/ethnicity was coded White, Black (non-Hispanic), other (two or more, non-Hispanic), and Hispanic. Education was coded less than high school, high school diploma, some college, and Bachelor’s degree and up. Income was classified as one of eight categories, consistent with prior analyses (Holman et al., 2020). Geographic regions of residence included Northeast, Midwest, South, and West.

Dependent Variables

Health-related worries.

Health-related worries were assessed by asking participants how often they “had fears that you will get very sick or die from the Coronavirus outbreak?” and “worried that someone you care about (e.g., family, close friends) will get very sick or die from the Coronavirus outbreak?” Items were assessed using a five-point scale from 1 (never) to 5 (all the time). Internal consistency was very good (α=.81).

Functional impairment.

Prior week functional impairment was assessed using four SF-36 items that measured physical and emotional impairment (Hays et al., 1993), on a five-point scale from 1 (none of the time) to 5 (all of the time). Internal consistency was very good (α=.87).

COVID-19-related acute stress.

COVID-19 outbreak-related acute stress symptoms were assessed using a 10-item modified version of the Acute Stress Disorder Scale 5 (Bryant et al., 2000). Items assessed symptoms from the previous week via a five-point scale from 1 (none at all) to 5 (a great deal). Internal consistency was very good (α=.87).

Statistical analysis

All analyses were conducted using STATA 16. Bivariate comparisons (t-tests for continuous variables and chi-square tests for categorical variables) illustrated significant differences between healthcare and non-healthcare essential workers. Three multivariate Ordinary Least Squares (OLS) regression analyses examined predictors of COVID-19-related health-related worries, functional impairment, and acute stress. Predictors were: healthcare worker status (healthcare worker=1; other essential worker=0), secondary stressors (lack of childcare due to COVID-19 school closures, lack of healthcare, lost wages; each coded 0=did not occur; 1=occurred), demographics (i.e., age, ethnicity, education, female gender, income), residential region, and cohort. Since the amount of missing data was extremely low (less than 1.5% in covariate-adjusted models) and Little’s Missing Completely at Random test was not significant (χ2 [9]=4.19, p=.89), listwise deletion was implemented. Post-hoc, interaction terms between key predictors and essential worker status (healthcare or non-healthcare) were examined; each was examined separately in individual models to conserve sample size, although results were identical when added into a combined model with all interaction terms.

Results

Table 1 presents descriptive statistics and between-group differences for demographic indicators and key covariates. Among all essential workers, difficulty meeting childcare needs was reported by 9.37% (n=169); 9.26% (n=167) reported inability to obtain necessary healthcare; and 21.96% (n=396) reported COVID-19-related lost or reduced wages. The means for acute stress, health-related worries, and functional impairment were 1.87 (SD= 0.72, range= 1–4.9), 2.53 (SD=1.04, range=1–5) and 1.58 (SD=0.81, range=1–5), respectively.

Table 1.

Characteristics of the sample (N= 1,821)

Essential worker characteristics Healthcare essential workers (n= 169) Non-healthcare essential workers (n=1,652) Test of between-group differences (non-healthcare vs healthcare essential workers) Effect size Cohen’s d (95% CI) or Cramér’s V
M(SD) M(SD)
Age 42.37(12.96) 43.88(13.27) t(1,819)=1.41 d=0.11(−0.05, 0.27)
n(%) n(%)
Race/Ethnicity
 White, Non-Hispanic 128(75.74%) 1,181(71.49%)
 Black, Non-Hispanic 16(9.47%) 170(10.29%)
 Other/2+ races, Non-Hispanic 12(7.10%) 139(8.41%)
 Hispanic 13(7.69%) 162(9.81%) χ2(3)=1.52 V=0.03
Education
 Less than high school 0(0%) 37(2.24%)
 High school graduate 5(2.96%) 279(16.89%)
 Some college 58(34.32%) 750(45.40)
 BA and above 106(62.72%) 586(35.47%) χ2(3)=57.06** V=0.18
Gender
 Male 44(26.04%) 751(45.46%)
 Female 125(73.96%) 901(54.54%) χ2(1)=23.52** V=0.11
Income
 Less than $10,000 2(1.18%) 66(4.00%)
 $10,000–$24,999 5(2.96%) 191(11.56%)
 $25,000–$49,000 21(12.43%) 403(24.39%)
 $50,000–$74,999 40(23.67%) 356(21.55%)
 $75,000–$99,999 32(18.93%) 272(16.46%)
 $100,000–$124,999 39(23.08%) 207(12.53%)
 $125,000–$149,999 15(8.88%) 89(5.39%)
 $150,000+ 15(8.88%) 68(4.12%) χ2(7)=47.61** V=0.16
Region
 Northeast 37(21.89%) 224(13.56%)
 Midwest 48(28.40%) 466(28.21%)
 South 45(26.63%) 550(33.29%)
 West 39(23.08%) 412(24.94%) χ2(3)=9.73* V=0.07
Cohort
 Cohort 1: 3/18/20–3/28/20 57(33.73%) 587(35.53%)
 Cohort 2: 3/29/20–4/7/20 61(36.09%) 533(32.26%)
 Cohort 3: 4/8/20–4/18/20 51(30.18%) 532(32.20%) χ2(2)=1.03 V=0.02
Secondary stressors
 Needed childcare for child because they were out of school 19(11.38%) 150 (9.17%) χ2(1)=.87 V=0.02
 I lost wages 51(30.54%) 345(21.09%) χ2(1)=7.90* V=0.07
 Unable to obtain necessary healthcare 12(7.19%) 155 (9.47%) χ2(1)=0.94 V=−0.02
Pre-pandemic mental health problems 23(13.61%) 282(17.07%) χ2(1)=1.31 V=−0.03
M(SD) M(SD)
Pre-pandemic physical health problems 0.65(0.89) 0.83(1.03) t(1819)=2.15* d=0.17(0.01, 0.33)
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*

p<.05,

**

p <.001

Note: Cohen’s d is presented for t-tests; Cramér’s V for χ2

Pre-pandemic mental health problems=emotional/nervous/psychiatric problem, anxiety disorder, depression (0=none; 1=one or more)

Pre-pandemic physical health problems= high cholesterol, hypertension, diabetes/high blood sugar, heart disease, stroke, cancer, lung disease, other diagnoses (0–8);

Tables 2, 3, and 4 present unadjusted and covariate-adjusted associations between predictors of health-related worries, functional impairment, and acute stress, respectively. In adjusted models, inability to obtain health insurance, lost wages, prior mental or physical health ailments, younger age, Hispanic ethnicity, and female gender were associated with acute stress, health-related worries, and functional impairment. Healthcare essential workers reported less functional impairment and acute stress compared to non-healthcare essential workers. Need for childcare was positively associated with acute stress symptoms, although not associated with health-related worries or functional impairment. Residents in the Northeast reported more health-related worries and acute stress than residents in the South. Those who completed the survey later reported more health-related worries, functional impairment, and acute stress compared to those who completed the survey in the earlier phases of the COVID-19 outbreak. Several interaction terms were significant. For functional impairment, need for childcare was moderated by essential worker status (b=−.50, 95% CI, −0.90, −0.11). For health-related worries and acute stress, lost wages was moderated by essential worker status, (b=−.42, 95% CI, −0.77, −0.07) and (b=−0.32, 95% CI, −0.56, −0.08), respectively. See Appendix B for full results including tables (Tables A1, A2, & A3) and graphs (Figures A1, A2, & A3).

Table 2.

Predictors of health-related worries in essential workers during COVID-19 (N=1,821)

Bivariate Associations Adjusted Multivariate Model
Variable Beta b 95% CI p beta b 95% CI p
Healthcare workera 0.01 0.03 −0.14, 0.19 .741 −0.01 −0.05 −0.21, 0.12 .564
Needed childcare 0.07 0.25 0.09, 0.41 .003 0.04 0.13 −0.04, 0.29 .126
Unable to obtain healthcare 0.16 0.56 0.39, 0.73 <.001 0.12 0.41 0.25, 0.58 <.001
Lost wages 0.11 0.29 0.17, 0.40 <.001 0.09 0.22 0.10, 0.33 <.001
Prior mental health dxb 0.14 0.38 0.25, 0.50 <.001 0.09 0.24 0.12, 0.37 <.001
Prior physical health dxc 0.04 0.04 −0.004. 0.09 .074 0.09 0.10 0.05, 0.15 <.001
Age −0.10 −0.01 −0.01, −0.004 <.001 −0.09 −0.01 −0.01, 0.003 .001
Race/Ethnicityd
 Black, Non-Hispanic 0.02 0.08 −0.08, 0.24 .352 0.01 0.03 −0.13, 0.20 .673
 Other/2+ races, Non-Hispanic 0.06 0.24 0.07, 0.42 .007 0.04 0.15 −0.02, 0.32 .094
 Hispanic 0.09 0.34 0.17, 0.50 <.001 0.08 0.29 0.13, 0.46 .001
Educatione
 High school graduate −0.16 −0.47 0.83, −0.11 .011 −0.09 −0.25 −0.60, 0.10 .155
 Some college −0.25 −0.52 −0.87, −0.18 .003 −0.16 −0.33 −0.67, 0.002 .051
 BA or above −0.22 −0.48 −0.83, −0.13 .007 −0.12 −0.25 −0.59, 0.09 .154
Female gender 0.16 0.33 0.24, 0.43 <.001 0.14 0.29 0.20, 0.39 <.001
Income −0.05 −0.03 −0.06, −0.005 .022 0.01 0.003 −0.03, 0.03 .828
Regionf
 Midwest −0.07 −0.16 −0.31, −0.002 .047 −0.06 −0.13 −0.28, 0.02 .085
 South −0.08 −0.18 −0.34, −0.03 .018 −0.09 −0.21 −0.35, −0.06 .006
 West −0.04 −0.10 −0.26, 0.05 .199 −0.06 −0.14 −0.30, 0.01 .070
Cohortg
 3/29/20–4/7/20 0.11 0.25 0.14, 0.37 <.001 0.10 0.21 0.10, 0.32 <.001
 4/8/20–4/18/20 0.11 0.24 0.12, 0.35 <.001 0.09 0.19 0.08, 0.30 .001
Constant − − − − 2.67 2.28, 3.08 <.001
Model statistics F(20, 1776)=10.24, p<.001, R2=.10
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a

Non-healthcare essential worker=0;

b

emotional/nervous/psychiatric problem, anxiety disorder, depression (0=none; 1=one or more);

c

high cholesterol, hypertension, diabetes/high blood sugar, heart disease, stroke, cancer, lung disease, other diagnoses (0–8);

d

White=0;

e

<high school=0;

f

Northeast=0;

g

Cohort 1: 3/18/20–3/28/20=0

Table 3.

Predictors of functional impairment in essential workers during COVID-19 (N=1,821)

Bivariate Associations Adjusted Multivariate Model
Variable Beta b 95% CI p Beta b 95% CI p
Healthcare workera −0.06 −0.17 −0.29, −0.04 .010 −0.06 −0.17 −0.30, −0.04 .009
Needed childcare 0.07 0.19 0.06, 0.32 .003 0.03 0.09 −0.03, 0.22 .145
Unable to obtain healthcare 0.21 0.59 0.46, 0.71 <.001 0.16 0.46 0.33, 0.58 <.001
Lost wages 0.09 0.19 0.10, 0.29 <.001 0.06 0.12 0.04, 0.21 .006
Prior mental health dxb 0.20 0.44 0.34, 0.54 <.001 0.16 0.35 0.25, 0.45 <.001
Prior physical health dxc 0.09 0.07 0.03, 0.11 <.001 0.12 0.10 0.06, 0.14 <.001
Age −0.09 −0.01 −0.01, −0.003 <.001 −0.08 −0.01 −0.01, −0.002 .001
Race/Ethnicityd
 Black, Non-Hispanic 0.05 0.14 0.01, 0.26 .029 0.04 0.10 −0.03, 0.22 .133
 Other/2+ races, Non-Hispanic 0.09 0.27 0.14, 0.41 <.001 0.05 0.15 0.02, 0.28 .027
 Hispanic 0.12 0.34 0.22, 0.47 <.001 0.10 0.28 0.15, 0.41 <.001
Educatione
 High school graduate −0.12 −0.27 −0.55, 0.01 .062 −0.05 −0.12 −0.39, 0.15 .391
 Some college −0.16 −0.26 −0.54, 0.01 .061 −0.08 −0.13 −0.39, 0.13 .339
 BA or above −0.17 −0.29 −0.56, −0.01 .041 −0.05 −0.09 −0.36, 0.17 .495
Female gender 0.09 0.16 0.08, 0.23 <.001 0.07 0.12 0.04, 0.19 .002
Income −0.09 −0.04 −0.07, −0.02 <.001 −0.02 −0.01 −0.03, 0.02 .522
Regionf
 Midwest −0.02 −0.04 −0.17, 0.08 .479 −0.02 −0.04 −0.15, 0.08 .542
 South −0.01 −0.01 −0.13, 0.11 .839 −0.03 −0.05 −0.17, 0.06 .362
 West 0.04 0.07 −0.05, 0.19 .251 0.01 0.01 −0.11, 0.13 .857
Cohortg
 3/29/20–4/7/20 0.05 0.09 −0.004, 0.18 .063 0.03 0.06 −0.03, 0.14 .215
 4/8/20–4/18/20 0.07 0.13 0.04, 0.22 .005 0.05 0.09 0.01, 0.18 .034
Constant − − − − 1.60 1.29, 1.92 <.001
Model statistics F(20, 1776)=12.64, p<.001, R2=.12
Open in a new tab
a

Non-healthcare essential worker=0;

b

emotional/nervous/psychiatric problem, anxiety disorder, depression (0=none; 1=one or more);

c

high cholesterol, hypertension, diabetes/high blood sugar, heart disease, stroke, cancer, lung disease, other diagnoses (0–8);

d

White=0;

e

<high school=0;

f

Northeast=0;

g

Cohort 3/18/20–3/28/20=0

Table 4.

Predictors of acute stress in essential workers during COVID-19 (N=1,821)

Bivariate Associations Adjusted Multivariate Model
Variable beta b 95% CI p beta b 95% CI P
Healthcare workera −0.02 −0.05 −0.16, 0.06 .390 −0.06 −0.14 −0.25, −0.27 .015
Needed childcare 0.14 0.35 0.24, 0.46 <.001 0.09 0.22 0.12, 0.33 <.001
Unable to obtain healthcare 0.19 0.46 0.35, 0.58 <.001 0.13 0.33 0.23, 0.44 <.001
Lost wages 0.15 0.26 0.18, 0.34 <.001 0.11 0.20 0.12, 0.28 <.001
Prior mental health dxb 0.18 0.35 0.27, 0.44 <.001 0.12 0.24 0.15, 0.33 <.001
Prior physical health dxc 0.01 0.01 −0.02, 0.04 .678 0.08 0.06 0.03, 0.09 .001
Age −0.17 −0.01 −0.01, −0.01 <.001 −0.14 −0.01 −0.01, −0.005 <.001
Race/Ethnicityd
 Black, Non-Hispanic 0.04 0.09 −0.02, 0.20 .121 0.02 0.04 −0.07, 0.15 .439
 Other/2+ races, Non-Hispanic 0.06 0.16 0.04, 0.28 .009 0.02 0.06 −0.05, 0.18 .297
 Hispanic 0.10 0.24 0.12, 0.35 <.001 0.08 0.18 0.07, 0.30 .001
Educatione
 High school graduate −0.19 −0.38 −0.63, −0.13 .003 −0.10 −0.19 −0.42, 0.04 .106
 Some college −0.25 −0.37 −0.61, −0.13 .002 −0.14 −0.20 −0.42, 0.02 .081
 BA or above −0.21 0.31 −0.55, −0.07 .011 −0.07 −0.10 −0.33, 0.13 .393
Female gender 0.18 0.26 0.19, 0.32 <.001 0.15 0.22 0.16, 0.29 <.001
Income −0.05 −0.02 −0.04, −0.002 .029 0.02 0.01 −0.01, 0.03 .325
Regionf
 Midwest −0.06 −0.09 −0.20, 0.01 .085 −0.05 −0.09 −0.19, 0.02 .098
 South −0.06 −0.10 −0.20, 0.01 .067 −0.08 −0.12 −0.22, −0.02 .015
 West 0.02 0.07 −0.14, 0.08 .633 −0.04 −0.06 −0.17, 0.04 .241
Cohortg
 3/29/20–4/7/20 0.09 0.14 0.06, 0.22 .001 0.07 0.10 0.03, 0.18 .007
 4/8/20–4/18/20 0.10 0.16 0.08, 0.24 <.001 0.08 0.11 0.05, 0.21 .001
Constant 1.99 1.72, 2.26 <.001
Model statistics F(20, 1782)=15.90, p<.001, R2=.15
Open in a new tab
a

Non-healthcare essential worker=0;

b

emotional/nervous/psychiatric problem, anxiety disorder, depression (0=none; 1=one or more);

c

high cholesterol, hypertension, diabetes/high blood sugar, heart disease, stroke, cancer, lung disease, other diagnoses (0–8);

d

White=0;

e

<high school=0;

f

Northeast=0;

g

Cohort 3/18/20–3/28/20=0

Discussion

We explored predictors of psychosocial outcomes in healthcare and non-healthcare essential workers working in face-to-face interactions during the early phase of the COVID-19 outbreak in the U.S. Results indicated secondary stressors (inability to obtain health insurance, lost wages), prior mental-health ailments, prior physical-health diagnoses, and demographic indicators (younger age, female gender, Hispanic ethnicity) were associated with greater functional impairment, ongoing worry, and acute stress. Effect sizes were largest for difficulty obtaining healthcare, lost wages, age, female gender, and prior mental health for acute stress; inability to obtain healthcare, and prior mental and physical health ailments for functional impairment; and inability to obtain health care, lost wages, Hispanic ethnicity, and female gender for health-related worries. Contrary to our hypothesis, non-healthcare essential workers reported more functional impairment and acute stress than healthcare workers, yet effect sizes were relatiely modest compared to other factors. Moreover, two stressors (needed childcare and lost wages) exhibited moderating effects, with negative outcomes exacerbated for non-healthcare workers.

Overall, distress and impairment was relatively low, indicating that while some reported distress and impairment, resilience early in the pandemic was common, in alignment with prior disaster research (Silver & Garfin, 2016). Indeed, people reported functional impairment, on average, between “not at all” and “a little of the time,” perhaps not surprising since these individuals were still working at the time of the assessment. Participants reported acute stress symptoms, on average, “just a little;” the mean for health related worries was highest of the variables assessed, with participants reporting these symptoms, on average, around the midpoint of the scale (i.e., between “rarely” and “sometimes”). Of note, the range and standard deviations indicate that despite resilience in many, some indiviudals reported distress and impairment at the scale maximums.

In a recent rapid review of research on healthcare workers employed during the COVID-19 pandemic, 24 studies identified risk factors for maladaptive psychological outcomes of healthcare workers – many of which paralleled the significant indicators presented herein, including female gender, younger age, and prior physical illness (De Kock et al., 2021). We expand this research by using data drawn from a probability-based sample of Americans that included both healthcare and non-healthcare essential workers. In the present study, female essential workers reported significantly higher amounts of all three psychosocial concerns compared to men, echoing previous studies conducted with COVID-19 healthcare workers (Tan et al., 2020) and viral epidemics (Serrano-Ripoll et al., 2020). As in prior epidemics, history of mental health ailments was associated with negative outcomes (Asmundson et al., 2020; Elbay et al., 2020); however, present analyses highlight the additional role of preexisting physical health conditions on psychosocial responses. Age was negatively correlated with health-related worries, functional impairment, and acute stress, potentially due to fewer years of work experience and preparation, such as medical students entering the workforce early (Konda et al., 2020), nurses with junior titles (Steege et al., 2009), or other entry-level jobs (Elbay et al., 2020). Outcomes among all essential workers worsened as the pandemic advanced, suggesting psychosocial difficulties mirrored the outbreak’s U.S. progression.

Residents from the U.S. Northeast experienced more health-related worries than Southern residents, aligning with regional outbreak severity during March and April 2020 when the data were collected (Konda et al., 2020). Hispanic ethnicity was positively associated with health-related worries, functional impairment, and acute stress. This aligns with data showing Hispanics, compared to other ethnicities, were more likely to live in a home where at least one worker was unable to work from home (Selden & Berdahl, 2020). Lack of childcare due to COVID-19 school closures was associated with higher acute stress symptoms, paralleling findings among a general sample that included healthcare workers that childcare concerns were associated with heighted anxiety and other worries (Hacimusalar et al., 2020). Notably, healthcare workers reported significantly less acute stress and functional impairment than non-healthcare essential workers, perhaps because healthcare workers have more protocols for working with infectious diseases, greater meaning in their work, or more experience on the job. Indeed, physicians in Izmir/Turkey who were actively treating COVID-19 had lower burnout and higher feelings of accomplishments compared to physicians treating other conditions (Dinibutun, 2020). Moreover, adequate protection training for nurses in China was associated with lower anxiety, acute stress, and depression in nurses during early phases of COVID-19 (Cai et al., 2020). These factors may be more likely explanations than job experience, as burnout and stress often increases in healthcare workers over their career trajectory (Cull et al., 2019).

Strengths and Limitations

Key strengths of this study include a large sample of U.S. essential workers, derived from an overall representative group of Americans recruited during COVID-19’s early progression in the U.S. Given the dearth of data on non-healthcare essential workers actively employed during COVID-19, our contributions to the literature demonstrate that this group may be critical to target with mental health recourses and outreach efforts. This is particularly crucial as society enters a new phase of the COVID-19 pandemic, where emerging variants are more contagious and community transmission remains high (Christie et al., 2021), yet essential workers are still required to engage in face-to-face interactions, potentially with fewer protections (e.g., relaxed mask mandates). Our analyses included pre-pandemic physical and mental health diagnosis data, allowing us to draw comparisons between prior diagnoses and present psychological symptomatology without the bias inherent in retrospective reporting.

We acknowledge several limitations. Our data on exposure and symptoms were collected concurrently. While the overall sample of Americans we surveyed was representative of the U.S and the subsample of essential workers we surveyed is likely proportional to their representation in the general population, we cannot consider this to be a representative sample of essential workers. While physical and mental health data were collected in advance of the pandemic, physical health data was available as count of potential ailments and mental health was available as a dichotomous yet/no variable. Finally, we did not assess specific job, seniority, or workplace safety precautions, which may further explain variability in outcomes.

Conclusions and Future Directions

To our knowledge, this is the first study evaluating psychosocial outcomes in both healthcare and non-healthcare U.S. essential workers during the COVID-19 pandemic using a probability-based design. While many workplaces have implemented COVID-19 mitigation strategies, health and safety concerns remain, and may be associated with psychosocial difficulties. Indeed, acute psychosocial responses to stress may portend deleterious downstream mental and physical health effects, including depression, anxiety, and cardiovascular problems, as well as reduced working capacity and lower self-reported overall health (Garfin et al., 2018). COVID-19-related psychological and occupational impairment could be eased by implementing reliable public health workplace policies (Tan et al., 2020) that encourage healthy coping strategies. Some hospitals have implemented innovative mental health and resilience-building centers for healthcare workers in response to the pandemic (DePierro et al., 2020), which non-healthcare sectors should consider enacting. Workers should be provided adequate benefits like health insurance and paid sick leave. The COVID-19 pandemic also ushered in advances in telehealth and online resources to improve self-care; these include individual and group psychotherapy and wellness apps that can be utilized on mobile devices (Garfin, 2020). Such resources may be valuable for workers as they allow for the safe delivery of interventions and greater convenience for scheduling around work hours. Attention should be paid to non-healthcare essential workers in addition to healthcare essential workers, as their likelihood for functional impairment may be heightened without corresponding supports. As COVID-19 becomes endemic, appropriate resources should be provided for workers who are most vulnerable to COVID-19 and as we strive to prepare for future outbreaks.

Supplementary Material

Final supplementary materials

Clinical Impact Statement.

Prior literature has documented healthcare essential workers’ adverse psychological responses during viral outbreaks including COVID-19; non-healthcare essential workers have been understudied. Between March 18, 2020 and April 18, 2020, we surveyed 1,821 United States residents (a subsample of a nationally representative sample of 6,514) still working in-person during the COVID-19 pandemic. Demographics, secondary stressors, non-healthcare occupation, and mental/physical health history were positively associated with acute stress, health-related worries, and functional impairment. As society adapts to COVID-19 and its evolving variants, essential workers may continue to be vulnerable. Adequate protection, targeted psychosocial services, and appropriate preparation for future outbreaks is crucial.

Acknowledgments

Research was funded by National Science Foundation RAPID grant SES 2026337. Dana Rose Garfin was supported by K01 MD013910. The study sponsor played no role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.

Footnotes

Authors report no conflicts of interest.

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